Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...

A new research paper describes a statistical framework that resolves significant calculation biases caused by artificial ...

If you've ever wondered whether an AI feature on your phone is doing anything useful, Ben Khalesi has probably asked the same question. He has covered AI and Android for Android Police since 2023, ...

Deep learning finds numerous applications in machine vision solutions, particularly in enhancing image analysis and recognition tasks. Algorithmic models can be trained to recognize patterns, shapes ...

Investigating the Most Effective Machine Learning Algorithm for Detecting Pneumonia in Chest X-Ray Scans. Pneumonia is a serious infection which affects the lungs. - teganstorm/dissertation-project ...

An interpretable machine learning framework combining Schrödinger optimization and SHAP analysis improved four-class ...

The current MA risk adjustment model has shortcomings, both in predictive accuracy and payment equity across the Medicare program, which could be mitigated using lessons from machine learning. MA ...

A scalable unsupervised machine learning framework categorizes complex urban microclimates from continuous radiant ...

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms—addressing a ...